Industrial automatic production scheduling system and method based on artificial intelligence

Abstract

The invention discloses an industrial automatic production scheduling system and method based on artificial intelligence, and belongs to the technical field of automatic production scheduling, and the method comprises the steps: obtaining the historical production record of each production line from a database, and analyzing the maximum productivity of each production line; real-time production records of all the production lines are obtained, and the predicted completion date and surplus characteristics of all the production lines are analyzed in combination with the maximum productivity of all the production lines; according to the product and the urgent amount of the urgent order, whether the urgent order can be inserted or not is analyzed in combination with the surplus features of each production line in the first production line set; if the urgent order can be inserted, analyzing the inserted orders and the distribution characteristics of the inserted orders according to the urgent delivery date of the urgent order in combination with the surplus characteristics of the production lines in the first production line set; according to the method, accurate evaluation of the productivity of the production line is realized, the accuracy and the real-time performance of scheduling are improved, meanwhile, emergency production requirements are flexibly met, the delivery cycle is shortened, and the customer satisfaction and the market competitiveness are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of automated production scheduling, and specifically relates to an industrial automated production scheduling system and method based on artificial intelligence. Background Art

[0002] With the development of today's society and the improvement of science and technology, the degree of automation in industrial production is getting higher and higher. More and more automated equipment is being applied to the production process, and the process is more perfect. However, more problems are coming along with it, among which the most prominent one is the production scheduling problem. Traditional scheduling methods rely on manual planning and adjustment of orders. As the volume of automated production orders increases, customers will place expedited orders, and manual scheduling will be used to implement inserted orders. However, manual scheduling is difficult to accurately control production demand, resulting in delayed delivery of inserted orders, which reduces customer trust and affects the development of the company. Therefore, people urgently need an industrial automation production scheduling system based on artificial intelligence to solve the above problems. Summary of the invention

[0003] The purpose of the present invention is to provide an industrial automation production scheduling system based on artificial intelligence to solve the problems raised in the above background technology.

[0004] In order to solve the above technical problems, the present invention provides the following technical solutions: An industrial automation production scheduling method based on artificial intelligence, the method comprising the following steps: S1. Obtain historical production records of each production line from a database, screen the historical production records to obtain a first record set, and classify the first record set according to products to obtain several product production sets; and analyze the maximum production capacity of each production line according to the product production sets; S2. Obtain the real-time production records of each production line from the database, match the order information of the corresponding orders of each production line, and analyze the expected completion date and surplus characteristics of each production line in combination with the maximum production capacity of each production line; S3. Filter out the first production line set based on the products of the expedited order; analyze whether the expedited order can be inserted based on the surplus characteristics of each production line in the first production line set and the expedited quantity of the expedited order; S4. If the expedited order cannot be inserted, a message indicating that the order cannot be inserted is sent; if the expedited order can be inserted, the expedited production volume of each production line is calculated based on the expedited delivery date of the expedited order and the surplus characteristics of each production line in the first production line set, and the inserted order and the allocation characteristics of each inserted order are analyzed to schedule production.

[0005] According to the above technical solution, step S1 includes: S1-1. Each time the production line runs, a historical production record is generated and stored in the database. The historical production record includes the product, production duration, production volume, and average load of the main equipment. According to the average load of the main equipment, a load threshold is set, and the historical production records with the average load of the main equipment less than or equal to the load threshold in the historical production records are screened out to form a first record set. S1-2. According to the type of the product, the historical production records in the first record set are divided into different product production sets. S1-3. Take a certain product production set as the target set. Extract any historical production record from the target set, calculate the ratio of the production volume to the production duration in this historical production record as the production capacity of this historical production record. Compare the production capacities of all historical production records of the same production line in the target set, and select the maximum value as the maximum production capacity of the production line for producing the corresponding product.

[0006] By screening historical production records and conducting production capacity analysis, abnormal data can be effectively excluded, ensuring the reliability and accuracy of the data. Taking the maximum production capacity of the production line as the reference basis for production capacity provides scientific data support for subsequent scheduling decisions, which helps to improve the accuracy and rationality of scheduling.

[0007] According to the above technical solution, the step S2 includes: S2-1. When the production line is running, a real-time production record of the production line is generated and stored in the database. The real-time production record includes the order number, the production duration that has been completed, and the production volume that has been completed. S2-2. Match the order information corresponding to the order of the production line according to the order number. The order information includes the order number, the product, the order quantity, the quantity that has been completed, and the agreed delivery date. S2-3. According to the real-time production record of a certain production line, calculate the ratio of the production duration that has been completed to the production volume that has been completed as the real-time output value of this production line. Calculate the value obtained by subtracting the quantity that has been completed from the order quantity of the order corresponding to this production line to obtain the remaining production volume of this production line. Calculate the ratio of the remaining production volume of this production line to the real-time output value to obtain the remaining production duration of this production line. Add the time stamp corresponding to the real-time production record of this production line to the remaining production duration of this production line to obtain the estimated completion date of this production line. Obtain the time length from the estimated completion date of this production line to the agreed delivery date of this order as the surplus time of this production line. Extract the maximum production capacity of this production line for producing the corresponding product as the surplus production capacity of this production line. Calculate the value obtained by multiplying the surplus time of this production line by the surplus production capacity to obtain the surplus production volume of this production line. Take the surplus production capacity and the surplus production volume of this production line as the surplus characteristics of this production line. Monitor the production status of the production line in real time, calculate the estimated completion date and surplus features, and give early warnings of potential production delay problems in a timely manner. By analyzing the real-time output value and surplus production capacity of the production line, dynamically evaluate the load status of the production line, provide accurate data support for the feasibility judgment of order insertion, and improve the flexibility and real-time performance of production scheduling.

[0008] According to the above technical solution, the step S3 includes: S3-1. Obtain rush orders from the database. The rush orders include products, rush quantities, and rush delivery dates; according to the time stamps corresponding to the rush orders, obtain the real-time production records of the production line and their corresponding surplus features from the database. S3-2. Divide the production lines in which the products in the real-time production records are the same as those in the rush orders and the agreed delivery dates of the corresponding orders are after the rush delivery dates into the first production line set; calculate the sum value of the surplus production quantities of all production lines in the first production line set according to the surplus production quantities of each production line in the first production line set, and judge it against the rush quantity of the rush order; if the sum value of the surplus production quantities of all production lines in the first production line set is greater than the rush quantity of the rush order, the rush order can be inserted; if the sum value of the surplus production quantities of all production lines in the first production line set is less than or equal to the rush quantity of the rush order, the rush order cannot be inserted. Combined with the rush quantity and delivery date of the rush order, accurately screen out the eligible production line set and evaluate whether it meets the order insertion conditions. This step can reasonably allocate production capacity in case of emergency, quickly respond to the urgent needs of customers, effectively improve the flexibility of the production plan, and reduce production conflicts and resource waste caused by improper scheduling.

[0009] According to the above technical solution, the step S4 includes: S4-1. If the rush order cannot be inserted, send a message indicating that the order cannot be inserted; if the rush order can be inserted, obtain the time length from the time stamp corresponding to the rush order to the rush delivery date of the rush order as the rush production duration; use the surplus production quantities of each production line in the first production line set as the rush production quantities of each production line. S4-2. Sort the production lines in the first production line set from large to small according to the sizes of the surplus production capacities of each production line in the first production line set; mark the production lines in sequence according to the sorted production lines, and count the sum value of the rush production quantities of all marked production lines, and stop marking when the sum value of the rush production quantities of all marked production lines is greater than the rush quantity of the rush order. Take the orders corresponding to the marked production lines as the inserted orders; take the rush production duration of the marked production lines as the allocated production duration of the inserted orders; take the rush production quantities of the marked production lines as the allocated production quantities of the inserted orders; take the allocated production duration and the allocated production quantity as the allocated features of the inserted orders. S4-3. When producing rush orders from the inserted orders, use the surplus production capacity of the production line corresponding to the inserted order as the production capacity standard, and the allocated production duration of the inserted order as the duration standard. Calculate the value obtained by multiplying the production capacity standard by the duration standard as the standard production volume of the inserted order. Calculate the difference between the standard production volume of the inserted order and the allocated production volume of the inserted order, and record it as the first production difference of the inserted order. If the first production differences of all inserted orders are greater than or equal to zero, then record the first production differences in the completed quantities of the corresponding inserted orders. If there exists an inserted order with a first production difference less than zero, then mark this inserted order as a shortage order, take the absolute value of the first production difference of the shortage order, and sum up the absolute values of the first production differences of all shortage orders as the shortage quantity. Extract the inserted orders with a first production difference greater than or equal to zero to form a sufficient order set. Sort the inserted orders in the sufficient order set from largest to smallest according to the size of the surplus production capacity of the production line corresponding to the inserted order. Extract the inserted orders in the sufficient order set in sequence according to the sorting, and sum up the corresponding first production differences of the extracted inserted orders, and record it as the compensation quantity. When the compensation quantity is greater than or equal to the shortage quantity, stop the extraction. Use the products produced by the extracted inserted orders as supplements for the rush orders, and the supplementary quantity is the corresponding first production difference of the inserted order. After using the products produced by the extracted inserted orders as supplements for the rush orders, the products produced by the shortage orders after the rush orders are delivered are used as supplements for the taken-out inserted orders, and the supplementary quantity is the shortage quantity corresponding to the shortage order.

[0010] Through task allocation and order insertion adjustment, ensure the timely delivery of rush orders and avoid interfering with the normal delivery of existing orders. Based on the sorting of the surplus production capacity of each production line, achieve the optimal allocation of rush production tasks, maximize the utilization rate of production line resources, improve the overall production efficiency, and optimize the balance and stability of scheduling.

[0011] An industrial automation production scheduling system based on artificial intelligence, which includes a data collection module, a data analysis module, a scheduling decision module, and a scheduling execution module. The data acquisition module is used to collect and store the historical production records and real-time production records of each production line, providing basic data support for the subsequent data analysis module and scheduling decision-making module; the data analysis module is used to screen and analyze the historical production records and real-time production records, calculate the production capacity, estimated completion date and surplus characteristics of each production line; the scheduling decision-making module is used to screen the production line set according to the product, urgent quantity and urgent delivery date of the urgent order, and combine the surplus characteristics of each production line in the production line set to judge the feasibility of inserting the urgent order, and feedback the judgment result; the scheduling execution module is used to analyze the allocation characteristics of the inserted order and each inserted order according to the urgent delivery date of the urgent order and the surplus characteristics of each production line in the first production line set when the urgent order can be inserted, ensuring the on-time delivery of the urgent order and reducing production conflicts.

[0012] According to the above technical solution, the data acquisition module includes a historical data unit and a real-time data unit; The historical data unit is used to collect and store the historical production records of each production line, including products, production duration, production quantity and average load of the main equipment; the real-time data unit is used to collect and store the real-time production records of each production line, including order numbers, production duration and production quantity already produced.

[0013] According to the above technical solution, the data analysis module includes a production capacity calculation unit and a surplus analysis unit; The production capacity calculation unit is used to screen the product production set according to the historical production records of each production line, and calculate and analyze the product production set to obtain the maximum production capacity of the production line for producing corresponding products; the surplus analysis unit is used to calculate the estimated completion date, surplus duration and surplus production quantity of each production line according to the real-time production records and historical production records.

[0014] According to the above technical solution, the scheduling decision-making module includes a production line screening unit and an order insertion evaluation unit; The production line screening unit is used to screen the first production line set according to the product and urgent delivery date of the urgent order, combined with the real-time production records and surplus characteristics; the order insertion evaluation unit is used to analyze the surplus production quantity of each production line in the first production line set, combined with the urgent quantity of the urgent order, to judge whether the urgent order can be inserted and send the judgment result.

[0015] According to the above technical solution, the scheduling execution module includes a task allocation unit and an order insertion adjustment unit; The task allocation unit is used to calculate the urgent production quantity that each production line can execute according to the ranking of the surplus production capacity of each production line, and mark the production lines to be inserted according to the ranking, and match the inserted orders and their allocated production quantities; the order insertion adjustment unit is used to adjust the production according to the inserted orders and their allocated production quantities to ensure that the order insertion does not affect the normal delivery of the order.

[0016] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: Through the screening of historical production records and production capacity analysis, combined with real-time production data, the present invention dynamically adjusts the production plan of the production line, realizes the accurate assessment of the production capacity of the production line, and improves the accuracy and real-time performance of scheduling; at the same time, through the urgent order insertion evaluation mechanism, according to the urgency volume, delivery date of the urgent order and the surplus characteristics of the production line, the present invention judges the feasibility of order insertion in real time, flexibly responds to urgent production needs, shortens the delivery cycle, improves customer satisfaction and market competitiveness; secondly, through the sorting of surplus production capacity of each production line and task allocation, the present invention realizes the optimal allocation of urgent orders, maximizes the utilization rate of production line resources, and optimizes the balance and stability of scheduling; in addition, through real-time monitoring of the production status of the production line and timely warning of potential production delay problems, combined with intelligent scheduling and autonomous optimization strategies, the present invention effectively reduces scheduling conflicts and risks, and improves the stability and practicality of the scheduling system. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The drawings are used to provide a further understanding of the present invention, and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention, and do not constitute a limitation to the present invention. In the drawings: Figure 1 is a schematic flow chart of an industrial automation production scheduling method based on artificial intelligence according to the present invention; Figure 2 is a schematic structural diagram of an industrial automation production scheduling system based on artificial intelligence according to the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0019] Please refer to Figure 1 , an industrial automation production scheduling method based on artificial intelligence, the method comprising the following steps: S1. Obtain the historical production records of each production line from the database, screen the historical production records to obtain a first record set, and classify the first record set according to products to obtain several product production sets; analyze the maximum production capacity of each production line according to the product production sets; According to the above technical solution, the step S1 includes: S1-1. Each time the production line runs, a historical production record is generated and stored in the database. The historical production record includes the product, production duration, production volume, and average load of the main equipment. According to the average load of the main equipment, a load threshold is set, and the historical production records with an average load of the main equipment less than or equal to the load threshold in the historical production records are screened out to form a first record set. S1-2. According to the type of the product, the historical production records in the first record set are divided into different product production sets. S1-3. Take a certain product production set as the target set. Extract any historical production record from the target set, calculate the ratio of the production volume to the production duration in this historical production record as the production capacity of this historical production record. Compare the production capacities of all historical production records of the same production line in the target set, and select the maximum value as the maximum production capacity of the production line for producing the corresponding product.

[0020] By screening historical production records and conducting production capacity analysis, abnormal data can be effectively excluded, ensuring the reliability and accuracy of the data. Taking the maximum production capacity of the production line as a reference for production capacity provides scientific data support for subsequent scheduling decisions, which helps improve the accuracy and rationality of scheduling.

[0021] S2. Obtain the real-time production records of each production line from the database, match the order information corresponding to the orders of each production line, and combine the maximum production capacities of each production line to analyze the estimated completion date and surplus characteristics of each production line. According to the above technical solution, the step S2 includes: S2-1. When the production line is running, a real-time production record of the production line is generated and stored in the database. The real-time production record includes the order number, the elapsed production duration, and the produced volume. S2-2. Match the order information corresponding to the order of the production line according to the order number. The order information includes the order number, product, order quantity, completed quantity, and agreed delivery date. S2-3. According to the real-time production record of a certain production line, calculate the ratio of the elapsed production duration to the produced volume as the real-time output value of this production line. Calculate the value obtained by subtracting the completed quantity from the order quantity of the order corresponding to this production line to obtain the remaining production volume of this production line. Calculate the ratio of the remaining production volume of this production line to the real-time output value to obtain the remaining production duration of this production line. Add the time stamp corresponding to the real-time production record of this production line to the remaining production duration of this production line to obtain the estimated completion date of this production line. Obtain the time length from the estimated completion date of the production line to the agreed delivery date of the order as the surplus time of the production line; extract the maximum production capacity of the production line for producing the corresponding product as the surplus production capacity of the production line; calculate the value obtained by multiplying the surplus time of the production line by the surplus production capacity to obtain the surplus production volume of the production line; use the surplus production capacity and surplus production volume of the production line as the surplus characteristics of the production line. Monitor the production status of the production line in real time, calculate the estimated completion date and surplus characteristics, and give early warnings of potential production delay problems in a timely manner. By analyzing the real-time output value and surplus production capacity of the production line, dynamically evaluate the load status of the production line, provide accurate data support for the feasibility judgment of order insertion, and improve the flexibility and real-time performance of production scheduling.

[0022] S3. Screen out the first production line set according to the products of the rush order; analyze whether the rush order can be inserted according to the surplus characteristics of each production line in the first production line set and the rush volume of the rush order. According to the above technical solution, the step S3 includes: S3-1. Obtain the rush order from the database, where the rush order includes products, rush volume, and rush delivery date; obtain the real-time production records of the production line and their corresponding surplus characteristics from the database according to the time stamp corresponding to the rush order. S3-2. Divide the production lines whose products in the real-time production records are the same as those of the rush order and the agreed delivery date of the corresponding order is after the rush delivery date into the first production line set; calculate the sum value of the surplus production volumes of all production lines in the first production line set according to the surplus production volumes of each production line in the first production line set, and judge it with the rush volume of the rush order; if the sum value of the surplus production volumes of all production lines in the first production line set is greater than the rush volume of the rush order, the rush order can be inserted; if the sum value of the surplus production volumes of all production lines in the first production line set is less than or equal to the rush volume of the rush order, the rush order cannot be inserted. Combined with the rush volume and delivery date of the rush order, accurately screen out the eligible production line set and evaluate whether it meets the order insertion conditions. This step can reasonably allocate production capacity in case of emergency, quickly respond to the urgent needs of customers, effectively improve the flexibility of the production plan, and reduce production conflicts and resource waste caused by improper scheduling. For example: The product of the rush order is A, the rush volume is 300, and the rush delivery date is 8 days later; In the real-time production record of production line 1, the product is A, the surplus production volume is 200 pieces, and the agreed delivery date of corresponding order 1 is 10 days later; in the real-time production record of production line 2, the product is A, the surplus production volume is 150 pieces, and the agreed delivery date of corresponding order 2 is 10 days later; in the real-time production record of production line 3, the product is B, the surplus production volume is 250 pieces, and the agreed delivery date of corresponding order 3 is 9 days later. For the products of the urgent order, production line 3 is excluded; according to the urgent delivery date, the agreed delivery date of order 1 is after the urgent delivery date, and the agreed delivery date of order 2 is filtered to be after the urgent delivery date. The first production line set is production line 1 and production line 2; The sum of the surplus production volumes of all production lines in the first production line set is 200 + 150 = 350; the sum of the surplus production volumes of all production lines in the first production line set, which is 350, is greater than the urgent volume of the urgent order, which is 300. Then, the urgent order can be inserted.

[0023] S4. If the urgent order cannot be inserted, send a message indicating that it cannot be inserted; if the urgent order can be inserted, based on the urgent delivery date of the urgent order, combined with the surplus characteristics of each production line in the first production line set, calculate the urgent production volume of each production line, and analyze the allocation characteristics of the order to be inserted and each order to be inserted, and schedule the production; According to the above technical solution, the step S4 includes: S4-1. If the urgent order cannot be inserted, send a message indicating that it cannot be inserted; if the urgent order can be inserted, obtain the time length from the time stamp corresponding to the urgent order to the urgent delivery date of the urgent order as the urgent production duration; use the surplus production volume of each production line in the first production line set as the urgent production volume of each production line; S4-2. Sort the production lines in the first production line set from largest to smallest according to the size of the surplus production capacity of each production line in the first production line set; mark the production lines in sequence according to the sorted production lines, and count the sum of the urgent production volumes of all marked production lines. Stop marking when the sum of the urgent production volumes of all marked production lines is greater than the urgent volume of the urgent order; Take the order corresponding to the marked production line as the order to be inserted; take the urgent production duration of the marked production line as the allocated production duration of the order to be inserted; take the urgent production volume of the marked production line as the allocated production volume of the order to be inserted; take the allocated production duration and the allocated production volume as the allocation characteristics of the order to be inserted; S4-3. When the order to be inserted produces the urgent order, use the surplus production capacity of the production line corresponding to the order to be inserted as the production capacity standard and the allocated production duration of the order to be inserted as the duration standard, and calculate the value obtained by multiplying the production capacity standard by the duration standard as the standard production volume of the order to be inserted; calculate the difference between the standard production volume of the order to be inserted and the allocated production volume of the order to be inserted, and record it as the first production difference of the order to be inserted; If the first production differences of all orders to be inserted are greater than or equal to zero, then record the first production difference in the completed volume of the corresponding order to be inserted; If there exists a first production difference of an order to be inserted that is less than zero, then mark the order to be inserted as an insufficient order, take the absolute value of the first production difference of the insufficient order, and count the sum of the absolute values of the first production differences of all insufficient orders as the insufficient volume; Extract the inserted orders whose first production difference is greater than or equal to zero to form a sufficient order set; sort the inserted orders in the sufficient order set from largest to smallest according to the surplus production capacity of the production line corresponding to the inserted order, and extract the inserted orders in the sufficient order set in sequence according to the sorting. Statistically sum the first production differences corresponding to the extracted inserted orders, which is recorded as the compensation amount; when the compensation amount is greater than or equal to the shortage amount, stop extraction. Use the products produced by the extracted inserted orders as supplements to the urgent orders, and the supplement amount is the first production difference corresponding to the inserted order. After using the products produced by the extracted inserted orders as supplements to the urgent orders, the products produced by the shortage orders after the delivery of the urgent orders are used as supplements to the extracted inserted orders, and the supplement amount is the shortage amount corresponding to the shortage orders. Through task allocation and order insertion adjustment, ensure the timely delivery of urgent orders and avoid interfering with the normal delivery of existing orders. Based on the sorting of the surplus production capacity of each production line, achieve the optimal allocation of urgent production tasks, maximize the utilization rate of production line resources, improve the overall production efficiency, and optimize the balance and stability of scheduling.

[0024] Please refer to Figure 2 , an industrial automation production scheduling system based on artificial intelligence, which includes a data collection module, a data analysis module, a scheduling decision module, and a scheduling execution module; The data collection module is used to collect and store the historical production records and real-time production records of each production line, providing basic data support for the subsequent data analysis module and scheduling decision module; the data analysis module is used to screen and analyze the historical production records and real-time production records, calculate the production capacity, estimated completion date, and surplus characteristics of each production line; the scheduling decision module is used to screen the production line set according to the products, urgent quantities, and urgent delivery dates of the urgent orders, and combine the surplus characteristics of each production line in the production line set to judge the feasibility of inserting urgent orders and feedback the judgment results; the scheduling execution module is used to analyze the inserted orders and the allocation characteristics of each inserted order according to the urgent delivery date of the urgent order and the surplus characteristics of each production line in the first production line set when the urgent order can be inserted, ensure the timely delivery of the urgent order, and reduce production conflicts.

[0025] According to the above technical solution, the data collection module includes a historical data unit and a real-time data unit; The historical data unit is used to collect and store the historical production records of each production line, including products, production duration, production quantity, and average load of the main equipment; the real-time data unit is used to collect and store the real-time production records of each production line, including order numbers, production duration already completed, and production quantity already completed.

[0026] According to the above technical solution, the data analysis module includes a production capacity calculation unit and a surplus analysis unit; The production capacity calculation unit is used to screen the product production set according to the historical production records of each production line, calculate and analyze the product production set, and obtain the maximum production capacity of the production line for producing corresponding products; the surplus analysis unit is used to calculate the estimated completion date, surplus duration and surplus production volume of each production line according to the real-time production records and historical production records.

[0027] According to the above technical solution, the scheduling decision module includes a production line screening unit and an order insertion evaluation unit; The production line screening unit is used to screen out the first production line set according to the products of the urgent order and the urgent delivery date, in combination with the real-time production records and surplus characteristics; the order insertion evaluation unit is used to analyze the surplus production volume of each production line in the first production line set, and analyze in combination with the urgent volume of the urgent order to determine whether the urgent order can be inserted, and send the judgment result.

[0028] According to the above technical solution, the scheduling execution module includes a task assignment unit and an order insertion adjustment unit; The task assignment unit is used to sort according to the surplus production capacity of each production line, calculate the urgent production volume that each production line can execute, mark the production lines to be inserted according to the sorting, match the orders to be inserted and their assigned production volumes; the order insertion adjustment unit is used to adjust the production according to the orders to be inserted and their assigned production volumes to ensure that the order insertion does not affect the normal delivery of the order. It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "including", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device.

[0029] Finally, it should be noted that the above are only the preferred embodiments of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. An industrial automation production scheduling method based on artificial intelligence, characterized in that: The method includes the following steps: S1. Obtain the historical production records of each production line from the database, screen the historical production records to obtain a first record set, and classify the first record set according to the products to obtain several product production sets; analyze the maximum production capacity of each production line according to the product production sets; S2. Obtain the real-time production records of each production line from the database, match the order information corresponding to the orders of each production line, and analyze the estimated completion date and surplus characteristics of each production line in combination with the maximum production capacity of each production line; S3. Screen out a first production line set according to the products of the urgent orders; analyze whether the urgent orders can be inserted according to the surplus characteristics of each production line in the first production line set and the urgency quantity of the urgent orders; S4. If the urgent order cannot be inserted, send a message indicating that it cannot be inserted; if the urgent order can be inserted, calculate the urgent production quantity of each production line according to the urgent delivery date of the urgent order and the surplus characteristics of each production line in the first production line set, and analyze the allocation characteristics of the inserted order and each inserted order, and schedule the production.

2. The industrial automation production scheduling method based on artificial intelligence according to claim 1, characterized in that: The step S1 includes: S1-1. Each time a production line runs, generate a historical production record and store it in the database; the historical production record includes products, production duration, production quantity, and average load of the main equipment; Set a load threshold according to the average load of the main equipment, and screen out the historical production records with the average load of the main equipment less than or equal to the load threshold in the historical production records to form a first record set; S1-2. Divide the historical production records in the first record set into different product production sets according to the types of products; S1-3. Take a certain product production set as the target set; extract any historical production record from the target set, calculate the ratio of the production quantity to the production duration in the historical production record as the production capacity of the historical production record; compare the production capacities of all historical production records of the same production line in the target set, and select the maximum value as the maximum production capacity of the production line for producing the corresponding product.

3. The industrial automation production scheduling method based on artificial intelligence according to claim 2, wherein: The step S2 includes: S2-1. When the production line is running, generate the real-time production record of the production line and store it in the database; the real-time production record includes the order number, the production duration already completed, and the production quantity already completed; S2-2. Match the order information corresponding to the order of the production line according to the order number, and the order information includes the order number, products, order quantity, quantity already completed, and agreed delivery date; S2-3. According to the real-time production record of a certain production line, calculate the ratio of the production duration already completed to the production quantity already completed as the real-time output value of the production line; calculate the value obtained by subtracting the quantity already completed from the order quantity of the order corresponding to the production line to obtain the remaining production quantity of the production line; calculate the ratio of the remaining production quantity of the production line to the real-time output value to obtain the remaining production duration of the production line; add the time stamp corresponding to the real-time production record of the production line to the remaining production duration of the production line to obtain the estimated completion date of the production line; Obtain the time length from the expected completion date of the production line to the agreed delivery date of the order as the surplus time of the production line; extract the maximum production capacity of the production line for producing the corresponding product as the surplus production capacity of the production line; calculate the value obtained by multiplying the surplus time of the production line by the surplus production capacity to obtain the surplus production volume of the production line; use the surplus production capacity and surplus production volume of the production line as the surplus characteristics of the production line.

4. The industrial automation production scheduling method based on artificial intelligence according to claim 3, wherein: The step S3 includes: S3-1. Obtain the rush orders from the database. The rush orders include products, rush quantities, and rush delivery dates; according to the time stamps corresponding to the rush orders, obtain the real-time production records of the production line and their corresponding surplus characteristics from the database. S3-2. Divide the production lines in which the products in the real-time production records are the same as the products in the rush orders and the agreed delivery dates of the corresponding orders are after the rush delivery dates into the first production line set; calculate the sum value of the surplus production volumes of all production lines in the first production line set according to the surplus production volumes of each production line in the first production line set, and judge it against the rush quantity of the rush order; if the sum value of the surplus production volumes of all production lines in the first production line set is greater than the rush quantity of the rush order, the rush order can be inserted; if the sum value of the surplus production volumes of all production lines in the first production line set is less than or equal to the rush quantity of the rush order, the rush order cannot be inserted.

5. An industrial automation production scheduling method based on artificial intelligence according to claim 4, characterized in that: The step S4 includes: S4-1. If the rush order cannot be inserted, send an information indicating that it cannot be inserted; if the rush order can be inserted, obtain the time length from the time stamp corresponding to the rush order to the rush delivery date of the rush order as the rush production time; use the surplus production volumes of each production line in the first production line set as the rush production volumes of each production line. S4-2. Sort the production lines in the first production line set from largest to smallest according to the magnitudes of the surplus production capacities of each production line in the first production line set; mark the production lines in sequence according to the sorted production lines, and count the sum value of the rush production volumes of all marked production lines, and stop marking when the sum value of the rush production volumes of all marked production lines is greater than the rush quantity of the rush order. Take the orders corresponding to the marked production lines as the inserted orders; take the rush production time of the marked production lines as the allocated production time of the inserted orders; take the rush production volumes of the marked production lines as the allocated production volumes of the inserted orders; use the allocated production time and allocated production volume as the allocated characteristics of the inserted orders. S4-3. When the inserted order produces the rush order, calculate the value obtained by multiplying the production capacity standard (the surplus production capacity of the production line corresponding to the inserted order) by the time standard (the allocated production time of the inserted order) as the standard production volume of the inserted order; calculate the difference between the standard production volume of the inserted order and the allocated production volume of the inserted order, and record it as the first production difference of the inserted order. If the first production differences of all inserted orders are greater than or equal to zero, record the first production differences in the completed quantities of the corresponding inserted orders. If there exists an inserted order with a first production difference less than zero, mark the inserted order as a shortage order, take the absolute value of the first production difference of the shortage order, and count the sum of the absolute values of the first production differences of all shortage orders as the shortage quantity. Extract the inserted orders with the first production difference greater than or equal to zero to form a sufficient order set; sort the inserted orders in the sufficient order set from largest to smallest according to the size of the surplus production capacity of the production lines corresponding to the inserted orders, and extract the inserted orders in the sufficient order set in sequence, and calculate the sum of the first production differences corresponding to the extracted inserted orders, which is recorded as the compensation amount; when the compensation amount is greater than or equal to the shortage amount, stop extraction; Use the products produced by the extracted inserted orders as supplements to the urgent orders, and the supplement amount is the first production difference corresponding to the inserted orders; After using the products produced by the extracted inserted orders as supplements to the urgent orders, the products produced by the shortage orders after the urgent orders are delivered are used as supplements to the extracted inserted orders, and the supplement amount is the shortage amount corresponding to the shortage orders.

6. An industrial automation production scheduling system based on artificial intelligence, which is used to implement an industrial automation production scheduling method based on artificial intelligence according to any one of claims 1-5, characterized in that: The system includes a data collection module, a data analysis module, a scheduling decision module and a scheduling execution module; The data collection module is used to collect and store the historical production records and real-time production records of each production line, and provide basic data support for the subsequent data analysis module and scheduling decision module; the data analysis module is used to screen and analyze the historical production records and real-time production records, and calculate the production capacity, estimated completion date and surplus characteristics of each production line; The scheduling decision module is used to screen the production line set according to the products, urgent quantities and urgent delivery dates of the urgent orders, and combine the surplus characteristics of each production line in the production line set to judge the feasibility of inserting urgent orders and feedback the judgment results; the scheduling execution module is used to analyze the allocation characteristics of the inserted orders and each inserted order according to the urgent delivery date of the urgent orders and combine the surplus characteristics of each production line in the first production line set when the urgent orders can be inserted.

7. An industrial automation production scheduling system based on artificial intelligence according to claim 6, characterized in that: The data collection module includes a historical data unit and a real-time data unit; The historical data unit is used to collect and store the historical production records of each production line, including products, production duration, production quantity and average load of the main equipment; the real-time data unit is used to collect and store the real-time production records of each production line, including order numbers, produced duration and produced quantity.

8. An industrial automation production scheduling system based on artificial intelligence according to claim 6, characterized in that: The data analysis module includes a production capacity calculation unit and a surplus analysis unit; The production capacity calculation unit is used to screen the product production set according to the historical production records of each production line, and calculate and analyze the product production set to obtain the maximum production capacity of the production line to produce the corresponding product; the surplus analysis unit is used to calculate the estimated completion date, surplus duration and surplus production quantity of each production line according to the real-time production records and historical production records.

9. An industrial automation production scheduling system based on artificial intelligence according to claim 6, characterized in that: The scheduling decision module includes a production line screening unit and an order insertion evaluation unit; The production line screening unit is used to screen the first production line set according to the products and urgent delivery dates of the urgent orders, and combine the real-time production records and surplus characteristics; the order insertion evaluation unit is used to analyze the surplus production quantities of each production line in the first production line set, and combine the urgent quantity of the urgent order to analyze whether the urgent order can be inserted and send the judgment result.

10. An industrial automation production scheduling system based on artificial intelligence according to claim 6, characterized in that: The scheduling execution module includes a task allocation unit and an order insertion adjustment unit; The task allocation unit is used to calculate the urgent production volume that each production line can execute according to the surplus production capacity ranking of each production line, mark the production lines to be inserted according to the ranking, match the inserted orders and their allocated production volumes; the order insertion adjustment unit is used to adjust the production according to the inserted orders and their allocated production volumes.

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